Structure-Preserving Unpaired Image Translation to Photometrically Calibrate JunoCam with Hubble Data

TL;DR

This paper introduces SP-I2I, a novel structure-preserving unpaired image translation method that calibrates JunoCam images using Hubble data, enabling detailed analysis of Jupiter's atmosphere by maintaining high-frequency spatial features.

Contribution

The paper presents a new unpaired image translation technique that preserves high-frequency details, specifically addressing resolution differences between JunoCam and HST for planetary imaging.

Findings

SP-I2I effectively calibrates JunoCam images using HST data.

State-of-the-art I2I methods are inadequate for this task.

The method improves remote sensing data quality for planetary analysis.

Abstract

Insights into Jupiter's atmospheric dynamics are vital for understanding planetary meteorology and exoplanetary gas giant atmospheres. To study these dynamics, we require high-resolution, photometrically calibrated observations. Over the last 9 years, the Juno spacecraft's optical camera, JunoCam, has generated a unique dataset with high spatial resolution, wide coverage during perijove passes, and a long baseline. However, JunoCam lacks absolute photometric calibration, hindering quantitative analysis of the Jovian atmosphere. Using observations from the Hubble Space Telescope (HST) as a proxy for a calibrated sensor, we present a novel method for performing unpaired image-to-image translation (I2I) between JunoCam and HST, focusing on addressing the resolution discrepancy between the two sensors. Our structure-preserving I2I method, SP-I2I, incorporates explicit frequency-space constraints designed to preserve high-frequency features ensuring the retention of fine, small-scale spatial structures - essential for studying Jupiter's atmosphere. We demonstrate that state-of-the-art unpaired image-to-image translation methods are inadequate to address this problem, and, importantly, we show the broader impact of our proposed solution on relevant remote sensing data for the pansharpening task.